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Comparison and interpretability of machine learning models to predict severity of chest injury.
Kulshrestha, Sujay; Dligach, Dmitriy; Joyce, Cara; Gonzalez, Richard; O'Rourke, Ann P; Glazer, Joshua M; Stey, Anne; Kruser, Jacqueline M; Churpek, Matthew M; Afshar, Majid.
Afiliação
  • Kulshrestha S; Burn and Shock Trauma Research Institute, Loyola University Chicago, Maywood, Illinois, USA.
  • Dligach D; Department of Surgery, Loyola University Medical Center, Maywood, Illinois, USA.
  • Joyce C; Center for Health Outcomes and Informatics Research, Health Sciences Division, Loyola University Chicago, Maywood, Illinois, USA.
  • Gonzalez R; Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA.
  • O'Rourke AP; Department of Computer Science, Loyola University Chicago, Chicago, Illinois, USA.
  • Glazer JM; Center for Health Outcomes and Informatics Research, Health Sciences Division, Loyola University Chicago, Maywood, Illinois, USA.
  • Stey A; Department of Public Health Sciences, Stritch School of Medicine, Loyola University Chicago, Maywood, Illinois, USA.
  • Kruser JM; Burn and Shock Trauma Research Institute, Loyola University Chicago, Maywood, Illinois, USA.
  • Churpek MM; Department of Surgery, Loyola University Medical Center, Maywood, Illinois, USA.
  • Afshar M; Department of Surgery, University of Wisconsin, Madison, Wisconsin, USA.
JAMIA Open ; 4(1): ooab015, 2021 Jan.
Article em En | MEDLINE | ID: mdl-33709067

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: JAMIA Open Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: JAMIA Open Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos